Data Scientist

The Los Angeles Lakers; El Segundo (CA); On-site; USD 100,000 - 115,000; Full time

Job summary

The Los Angeles Lakers seek a Data Scientist, Analytics Strategy, to develop, test, and maintain predictive models for player evaluation, roster construction, and in-game strategy within the Analytics Strategy team. You will partner with Software Development for visualizations and with Data Engineering for data onboarding.

Responsibilities include applying ML and statistics to basketball data, delivering production-ready models, and translating results into actionable decisions for Basketball

Qualifications

• 3+ years of professional experience in a data science or machine learning role.
• Proficiency in Python or equivalent language for end-to-end model development.
• Experience using modern ML and deep learning techniques (e.g. scikit-learn, TensorFlow, PyMC).
• Expertise with large data sets (e.g. PySpark, SQL); willingness to work with geolocation tracking data and biomechanical data.
• Familiarity with distributed computing and cloud-first principles.
• Ability to write clean code; proficient with version control (Git).
• Experience with time series/ probabilistic forecasting, MLOps and GPU computing is a plus.
• Experience with version control (Git).
• Best judgment on role and prudent use cases of AI to augment data science workflows.

Responsibilities

• Utilize statistical analysis, machine learning, and predictive modeling for Basketball Operations.
• Develop production-level models from exploration to deployment.
• Integrate data sources and onboard new data vendors.
• Create new analyses and summarize data for internal stakeholders (G League, Player Health, NBA Draft).
• Collaborate with Data Engineering to onboard data and maintain models; work with Software Development to build visualizations and apps.

Skills

Statistical analysis

Machine learning

Education

Bachelor’s in Statistics/Computer Science

Tools

Python

PySpark

SQL

scikit-learn

TensorFlow

PyMC

Git

Job description

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Data Scientist

Basketball Ops - Analytics Full Time El Segundo, CA, US

3 days ago Requisition ID: 1115

Salary Range: $100,000.00 To $115,000.00 Annually

Title:Data Scientist, Analytics Strategy

Department:Analytics Strategy, Basketball Operations

Reports to:Vice President, Analytics Strategy

Manages:None

Position Summary:The Data Scientist, Analytics Strategy is a critical member of the Analytics Strategy team, responsible for developing, testing, and maintaining predictive models and metrics for player evaluation, roster construction, player development, and in-game strategy. They will work with the Software Development team to create data visualizations and applications to assist in the consumption of results, and with the Data Engineering team to perform data onboarding and updating of models and metrics. The Data Scientist will collaborate with the other Data Scientists on the Analytics Strategy team to drive predictive value to aid decision-making across the entirety of Basketball Operations.

Essential Functions (Duties & Responsibilities**):

• Utilize statistical analysis, machine learning, and predictive modeling techniques to provide solutions and predictive power for Basketball Operations
• Drive development of production-level models — from exploratory data analysis and problem framing through model validation and deployment
• Integrate novel research, basketball metrics, and models into existing and new applications; onboard and evaluate new data vendors
• Originate innovative ways to analyze / summarize data from internal stakeholders (e.g. G League, Player Health, NBA Draft)
• Operate in both the ad-hoc and the long-term, creating new research and sustainable solutions as necessary in collaboration with the rest of the Basketball Operations department
• Manipulate and leverage large data for analysis and modeling; source, process, and understand new datasets that may aid in potential evaluations
• Translate data-driven results into actionable basketball decisions and recommendations

**Duties and Responsibilities subject to change based on organizational needs and direction from management.

Education:

• Bachelor’s in Statistics, Computer Science, or a related field, or equivalent academic or professional experience

Minimum Qualifications:

• 3+ years of professional experience in a data science or machine learning role
• Proficiency in Python or equivalent language for end-to-end model development
• Experience using modern machine learning and deep learning techniques (e.g. scikit-learn, TensorFlow, PyMC) to build robust models
• Expertise with techniques to analyze and use large data sets (e.g. PySpark, SQL); willingness to work with geolocation tracking data and biomechanical data
• Familiarity with distributed computing and cloud-first principles
• Ability to write clean and efficient code; proficiency with version control and code modularization
• Experience with time series/probabilistic forecasting, MLOps and GPU computing is a plus
• Experience with version control (e.g. Git)
• Best judgment on role and prudent use cases of AI to augment data science workflows

Other Qualifications:

• Adaptable, eager to self-learn new technical skills
• Knowledge of and passion for NBA basketball

Location:El Segundo (office M‑F), and other occasional off‑site events

Travel:Less than 5% of the time

Hours:Full-time.Must be available to work evenings, weekends, and holidays as reasonably required

The pay range for this role is $100,000 - $115,000 annually. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience and certifications. In addition to those factors, we consider the relative pay of our current employees in similar positions when making a final offer.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.